AI Architect

Infosys Consulting; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Infosys Consulting seeks an AI Architect with 8+ years to design and deliver AI-driven solutions for enterprise clients in Bengaluru. You will lead data scientists and AI/ML engineers, partner with PMs/POs/SMEs, and translate complex business challenges into scalable AI capabilities.

You will guide governance, best practices, and architecture strategies, while contributing to business development and thought leadership in Infosys Consulting’s Enterprise AI offerings.

Qualifications

• Strong understanding of designing, integrating, and managing complex AI and enterprise infrastructure solutions.
• Proficiency in LangChain for developing AI/GenAI solutions.
• Solid understanding of REST APIs, their design, development, and integration.
• Bachelor's or Master's degree in CS/Data Science/AI or related field; PhD preferred.

Responsibilities

• Define and communicate strategy for large-scale AI, GenAI, and Agentic AI implementations across delivery teams.
• Design and implement AI/ML architectures and solutions meeting business/technical needs.
• Lead development and deployment of AI/ML and GenAI solutions using LangChain and related frameworks.
• Architect and develop agentic AI systems using CrewAI, LangGraph, or proprietary platforms.
• Drive REST API integration within AI ecosystems and oversee full solution lifecycle.

Skills

Solution Architecture

LangChain

REST APIs

Python

TensorFlow

Cloud Platforms

Data Analysis

Machine Learning Algorithms

NLP

SQL

Big Data (Hadoop/Spark)

Project Management

Education

Bachelor's or Master's in Computer Science / Data Science / AI

PhD preferred

Tools

LangChain

CrewAI

LangGraph

Azure DevOps

GitHub Actions

Job description

Infosys Consulting, the management consulting arm of Infosys, is seeking an AI Architect with 8+ years of experience in AI, ML, GenAI, and Agentic AI. The role involves designing and delivering AI-driven solutions, leading teams of data scientists and AI/ML engineers, collaborating with business stakeholders, and translating complex business challenges into scalable AI solutions. The candidate will work closely with Product Managers, Product Owners, and SMEs to define and implement best-in class AI capabilities while staying current with emerging technologies. As part of the Advanced Enterprise AI Consulting Practice, the successful candidate will engage directly with clients to identify automation opportunities, drive business value, and strengthen competitive advantage. The ideal candidate will combine strong technical and solution-design expertise with analytical thinking, stakeholder management, and execution excellence. In addition to client delivery, they will contribute to business development, thought leadership, and the evolution of Infosys Consulting’s Enterprise AI offerings, while benefiting from significant opportunities for professional growth and impact.

Responsibilities

• Define and communicate the strategy for large-scale AI, GenAI, and Agentic AI implementations, ensuring alignment across delivery teams.
• Design and implement AI/ML architectures and solutions that meet business and technical requirements.
• Lead the development and deployment of AI/ML and GenAI solutions using LangChain and related frameworks.
• Architect and develop agentic AI systems using frameworks such as CrewAI, LangGraph, or proprietary platforms.
• Drive integration of REST APIs within AI, GenAI, and Agentic AI ecosystems.
• Oversee the full AI solution lifecycle, from planning and development through testing and deployment.
• Design and automate CI/CD pipelines using Azure DevOps, GitHub Actions, or equivalent tools.
• Collaborate with business stakeholders to define scope, features, standards, and best practices.
• Evaluate architectural alternatives and provide guidance on trade-offs, risks, and benefits.
• Ensure AI solutions are scalable, secure, resilient, and built using reusable design patterns.
• Define technology capabilities required for scalable data science and data platform initiatives.
• Provide technical leadership and strategic direction for AI, GenAI, and Agentic AI solutions.
• Mentor team members, guide technical decisions, and ensure solutions deliver measurable business value.
• Promote AI governance, best practices, standards, and data management principles.
• Assess data architecture and integration approaches to identify optimization opportunities.
• Lead the design and deployment of cost-effective multi-cloud AI solutions across engagements and programs.
• Develop proposals and communicate recommendations effectively to senior stakeholders.
• Contribute thought leadership and innovation across the Enterprise AI community.

Required Skills

• Solution Architecture: The candidate must have a strong understanding of designing, integrating, and managing complex AI and enterprise infrastructure solutions.
• LangChain: Proficiency in LangChain is essential. The candidate should be capable of developing and implementing AI and GenAI solutions using the framework.
• REST APIs: The candidate should have a solid understanding of REST APIs, including their design, development, integration, and management.
• Education: The candidate must hold a Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field. A PhD is preferred.

Preferred Skills

• Python: Knowledge of Python, a popular language for AI and ML, is beneficial.
• TensorFlow: Experience with TensorFlow, an open-source platform for machine learning, is a plus.
• Cloud Platforms: Familiarity with cloud platforms like AWS, Google Cloud, or Azure is advantageous.
• Data Analysis: Skills in data analysis can help in understanding and interpreting AI/ML data.
• Machine Learning Algorithms: Understanding various machine learning algorithms is beneficial.
• Deep Learning: Knowledge of deep learning methodologies can be a plus.
• Natural Language Processing: Experience with NLP can be beneficial for certain AI/ML projects.
• Big Data Technologies: Familiarity with big data technologies like Hadoop, Spark, etc. can be advantageous.
• SQL: Knowledge of SQL for database management can be a plus.
• Project Management: Skills in project management can help in overseeing AI/ML projects from inception to completion.